燃料效率
车辆路径问题
布线(电子设计自动化)
计算机科学
遗传算法
数学优化
消费(社会学)
运筹学
运输工程
汽车工程
工程类
计算机网络
数学
社会科学
机器学习
社会学
标识
DOI:10.1061/9780784479896.001
摘要
This study aims to investigate the green vehicle routing problem (GVRP), which considers stochastic traffic speeds, so that fuel consumption and emissions can be reduced. Considering a heterogeneous fleet, the fuel consumption rate differs due to several factors, such as vehicle types and conditions, travel speeds, roadway gradients, and payloads. A mathematical model was proposed to deal with the GVRP, and its objective is to minimize the sum of the fixed costs and the expected fuel consumption costs. A customized genetic algorithm was proposed for solving the model. The computational experiments confirm the efficiency of the algorithm and show that the solution of GVRP is quite different from that of the traditional vehicle routing problem. The proposed model and algorithm are capable of suggesting a guidance for green logistics service providers to adopt a beneficial vehicle routing plan so as to eventually achieve a low economic and environmental cost.
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